Translating Data Into Information that Changes Us

Data are a whole lot of meaningful patterns. We can generate data indefinitely, we can exchange data forever… we can store data, retrieve data and file them away. All this is great fun and maybe useful, maybe lucrative, but we have to ask why. The purpose is regulation and that means translating data into information. Information is what changes us. My purpose is to effect change – to impart information.

I think that’s not a bad interpretation at all and for the most part I think I would agree with it. Data is in essence a form of statistic, or perhaps that may be the other way around. Regardless, from data or statistics comes human interpretation, visualization, or a level of conceptualization which brings about an idea. Not sure if I am oversimplifying…

So the question remains, how do we go about “turning data into information”? I think one key ingredient that is often missing in data visualizations is a meaningful background so that the data in the foreground has a frame of reference.

I recently went to Design and the Elastic Mind at MoMA and like you, I was also most excited by the data visualization portion of the exhibit. I left feeling reaffirmed that it’s only a matter of time before visualizations become a mainstream way of exploring and absorbing information.

I often feel a tinge of disappointment with visualizations that aren’t grounded in space or time. They always feel harder to penetrate and therefore less engaging. “There sure are lots of complex relationships going on here,” I think to myself. I’m mesmerized for a few moments by its elegance, but eventually I walk away, unsure of what *information* I was supposed to get out of it.

Visualizations grounded in maps, timelines and calendars on the other hand, always draw me in because the semantic-rich backdrop gives me an easy way to start parsing patterns in the data.

Without this kind of context, it’s difficult to get started on querying the visualization. There are too many axes to take into consideration, where do I begin?

This is not to say that time and space are the only interesting axes with which to build a frame of reference. On the contrary, I wish I knew of more examples of data visualizations that are not built on maps or timelines, and yet are grounded in a semantic space.

so i know a little about stafford beer. he was a cyberneticist, specializing in management science. among his many claims to fame is his design of a cybernetic system to transition chile to socialism (at the request of allende’s govt).

this quote is cute in part because he’s taking a nonstandard view of “information.” that is, shannon defined information w/o thinking about the meaning of messages. by reintroducing meaning into the definition of information, he was doing something interesting. but it doesn’t come across in an isolated quote. kate hayles has a nice take on shannon in her books…

the image is also from beer; in “platform for change” he wrote a fair bit about how data should be collected from people… that the government was doing a sloppy job of it and it left people exposed to a host of abuses.

and yes, the book is a collection of his speeches and they are certainly eclectic. but he’s a good read…